bootstrap.pml

0th

Percentile

Bootstrap

bootstrap.pml performs (non-parametric) bootstrap analysis and bootstrap.phyDat produces a list of bootstrapped data sets. plotBS plots a phylogenetic tree with the with the bootstrap values assigned to the (internal) edges.

Keywords
cluster
Usage
bootstrap.pml(x, bs = 100, trees = TRUE, multicore = FALSE,
  mc.cores = NULL, ...)

bootstrap.phyDat(x, FUN, bs = 100, multicore = FALSE, mc.cores = NULL, jumble = TRUE, ...)

plotBS(tree, BStrees, type = "unrooted", bs.col = "black", bs.adj = NULL, p = 50, frame = "none", ...)

Arguments
x

an object of class pml or phyDat.

bs

number of bootstrap samples.

trees

return trees only (default) or whole pml objects.

multicore

logical, whether models should estimated in parallel.

mc.cores

The number of cores to use during bootstrap. Only supported on UNIX-alike systems.

further parameters used by optim.pml or plot.phylo.

FUN

the function to estimate the trees.

jumble

logical, jumble the order of the sequences.

tree

The tree on which edges the bootstrap values are plotted.

BStrees

a list of trees (object of class "multiPhylo").

type

the type of tree to plot, so far "cladogram", "phylogram" and "unrooted" are supported.

bs.col

color of bootstrap support labels.

bs.adj

one or two numeric values specifying the horizontal and vertical justification of the bootstrap labels.

p

only plot support values higher than this percentage number (default is 80).

frame

a character string specifying the kind of frame to be printed around the bootstrap values. This must be one of "none" (the default), "rect" or "circle".

Details

It is possible that the bootstrap is performed in parallel, with help of the multicore package. Unfortunately the multicore package does not work under windows or with GUI interfaces ("aqua" on a mac). However it will speed up nicely from the command line ("X11").

Value

bootstrap.pml returns an object of class multi.phylo or a list where each element is an object of class pml. plotBS returns silently a tree, i.e. an object of class phylo with the bootstrap values as node labels. The argument BStrees is optional and if not supplied the tree with labels supplied in the node.label slot.

References

Felsenstein J. (1985) Confidence limits on phylogenies. An approach using the bootstrap. Evolution 39, 783--791

Penny D. and Hendy M.D. (1985) Testing methods evolutionary tree construction. Cladistics 1, 266--278

Penny D. and Hendy M.D. (1986) Estimating the reliability of evolutionary trees. Molecular Biology and Evolution 3, 403--417

See Also

optim.pml, pml, plot.phylo, nodelabels,consensusNet and SOWH.test for parametric bootstrap

Aliases
  • bootstrap.pml
  • bootstrap.phyDat
  • plotBS
Examples
# NOT RUN {
# }
# NOT RUN {
data(Laurasiatherian)
dm <- dist.logDet(Laurasiatherian)
tree <- NJ(dm)
# NJ
set.seed(123)
NJtrees <- bootstrap.phyDat(Laurasiatherian,
     FUN=function(x)NJ(dist.logDet(x)), bs=100)
treeNJ <- plotBS(tree, NJtrees, "phylogram")

# Maximum likelihood
fit <- pml(tree, Laurasiatherian)
fit <- optim.pml(fit, rearrangement="NNI")
set.seed(123)
bs <- bootstrap.pml(fit, bs=100, optNni=TRUE)
treeBS <- plotBS(fit$tree,bs)

# Maximum parsimony
treeMP <- pratchet(Laurasiatherian)
treeMP <- acctran(treeMP, Laurasiatherian)
set.seed(123)
BStrees <- bootstrap.phyDat(Laurasiatherian, pratchet, bs = 100)
treeMP <- plotBS(treeMP, BStrees, "phylogram")
add.scale.bar()

# export tree with bootstrap values as node labels
# write.tree(treeBS)
# }
# NOT RUN {
# }
Documentation reproduced from package phangorn, version 2.5.5, License: GPL (>= 2)

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